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Trade frequency

How many trades a strategy produces per unit of time, which converts a per-trade edge into an annual return and a cost bill.

Frequency is the multiplier on everything. At plus 0.25R per trade and 0.8% risk, 50 trades a year returns roughly 10% before compounding; 250 trades returns roughly 50%. It also multiplies commissions, spread and slippage by the same factor.

Higher frequency has one genuine statistical advantage: it produces a usable sample-size far sooner. A strategy with 300 trades a year is evaluable in eighteen months; one with 20 trades a year needs a decade to reach the same confidence, which is why long-horizon discretionary approaches are so hard to validate.

Frequency should be an output of the strategy rather than a target. When a trader decides to trade more, the added trades come from the bottom of the setup quality distribution, and their expectancy is typically zero or negative. See overtrading and trade-frequency-cap.

Related: expectancy-per-unit-time, trade-frequency-cap, sample-size-for-edge, overtrading

See it drawn

Original diagrams for the ideas on this page. Illustrative, not real market data.

The spread of outcomes behind an expectancyA histogram of forty trades: a tall block of small losses on the left, a low spread of larger wins on the right, and a line marking the average outcome.NUMBER OF TRADES051024 LOSSES, AVG −$20016 WINS, AVG +$600EXPECTANCY +$120−$400−$200$0+$200+$400+$600+$800PROFIT OR LOSS PER TRADEexpectancy = (40% × $600) − (60% × $200) = +$120 per trade
Expectancy: the average trade. Forty trades sorted by outcome: 24 small losses and 16 larger wins. Weighting each side by how often it happens gives the average result per trade, marked here by the dashed line at +$120.

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